Gaussian beam migration: Prestack, common‐shot, TTI, true amplitude in angular domain

Virgilio, M.; Re, Simone; Colombo, Daniele

doi:10.1190/1.3059330

Cited by 3 publications

(2 citation statements)

References 3 publications

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“…Today, we can encounter studies on traveltime tomography, migration and inversion that take anisotropy into account (Ball 1995; Brenders et al 2008; Fowler et al 2008; Lecomte & Kaschwich 2008; Lesage et al 2008; Pratt et al 2008; Virgilio et al 2008; Whiteside et al 2008). Most of these studies are based on acoustic wave equations.…”

Section: Introductionmentioning

confidence: 99%

Frequency-domain elastic full waveform inversion for VTI media

Lee

Koo

Min

et al. 2010

Geophysical Journal International

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S U M M A R YTo describe subsurface structures in anisotropic media properly, particularly in transversely isotropic media with a vertical symmetry axis (VTI), which frequently appear in sedimentary basin environments, we develop a frequency-domain elastic full waveform inversion algorithm for 2-D VTI media. The inversion algorithm is based on the cell-based finite-difference modelling method and the adjoint state of the wave equation.Because the anisotropic inversion for VTI media deals with more elastic constants than the isotropic inversion, it is more prone to obtain local minimum solutions. For this reason, we may not succeed in properly describing the elastic constants of subsurface media if we only apply the standard inversion techniques to anisotropic waveform inversion. To compensate for the ill-posedness of the anisotropic waveform inversion, we couple elastic constants C 11 and C 33 based on Thomsen's relationship, which is also supported by the sensitivity analysis with respect to the parameters. To enhance the inversion results, we apply the frequency-selection strategy, moving from lower to higher frequencies and we carry out the inversion process over two stages. In both stages, all of the elastic constants are simultaneously optimized, as is done in the conventional waveform inversion. However, we only accept the inversion results for C 11 , C 33 and C 44 at the first stage, which will be used as the starting models for the second stage and C 13 is reinitialized as a linearly increasing model. We apply our waveform inversion algorithm to a simple 3-layered model and a part of the overthrust model. For the 3-layered model, the first inversion stage is enough to yield reasonable inversion results for all of the elastic constants. For the overthrust model, the second stage is needed to enhance the inversion results for C 13 .

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Section: Introductionmentioning

confidence: 99%

Frequency-domain elastic full waveform inversion for VTI media

Lee

Koo

Min

et al. 2010

Geophysical Journal International

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“…Gaussian beam migration has proved successful in migrating complex models, in which multi-arrivals, caustics and shadows are prevalent (Virgilio et al, 2008;Cai et al, 2011;Zhang et al, 2011).…”

Section: Kirchhoff Migrationmentioning

confidence: 99%

Least-squares Reverse-time Migration

Yao¹,

Jakubowicz²

2012

Proceedings

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Conventional migration methods, including reverse-time migration (RTM) have two weaknesses: first, they use the adjoint of forward-modelling operators, and second, they usually apply a crosscorrelation imaging condition to extract images from reconstructed wavefields. Adjoint operators, which are an approximation to inverse operators, can only correctly calculate traveltimes (phase), but not amplitudes. To preserve the true amplitudes of migration images, it is necessary to apply the inverse of the forward-modelling operator. Similarly, crosscorrelation imaging conditions also only correct traveltimes (phase) but do not preserve amplitudes. Besides, the examples show crosscorrelation imaging conditions produce strong sidelobes. Least-squares migration (LSM) uses both inverse operators and deconvolution imaging conditions. As a result, LSM resolves both problems in conventional migration methods and produces images with fewer artefacts, higher resolution and more accurate amplitudes. At the same time, RTM can accurately handle all dips, frequencies and any type of velocity variation. Combining RTM and LSM produces least-squares reverse-time migration (LSRTM), which in turn has all the advantages of RTM and LSM.In this thesis, we implement two types of LSRTM: matrix-based LSRTM (MLSRTM) and non-linear LSRTM (NLLSRTM). MLSRTM is a matrix formulation of LSRTM and is more stable than conventional LSRTM; it can be implemented with linear inversion algorithms but needs a large amount of computer memory. NLLSRTM, by contrast, directly expresses migration as an optimisation which minimises the ‫ܮ‬ 2 norm of the residual between the predicted and observed data. NLLSRTM can be implemented using non-linear gradient inversion algorithms, such as non-linear steepest descent and non-linear conjugated-gradient solvers.We demonstrate that both MLSRTM and NLLSRTM can achieve better images with fewer artefacts, higher resolution and more accurate amplitudes than RTM using three synthetic examples. The power of LSRTM is also further illustrated using a field dataset. Finally, a simple synthetic test demonstrates that the objective function used in LSRTM is sensitive to errors in the migration velocity.As a result, it may be possible to use NLLSRTM to both refine the migrated image and estimate the migration velocity.

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Near-surface and anisotropy modeling for efficient land seismic depth imaging in low-relief geology

et al. 2017

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Prestack depth migration of land data presents unique characteristics and challenges that distinguish it from the workflows applied for marine data. Such unique characteristics are primarily related to the near surface. In areas of low-relief geology, near-surface velocity variations can obscure the reservoir structure. The remaining deeper earth model section has good lateral continuity and can be described effectively by smooth velocity fields. Strategies for estimating the near-surface effects and incorporating them into a processing workflow are of primary importance for the successful depth imaging of land seismic data. The second important aspect of a depth imaging workflow is that the seismic image must honor the well markers or formation tops. The subhorizontal fine-scale layering of low-relief structures can cause anisotropy that needs to be taken into account to achieve accurate well ties and good image quality. We have evaluated the application of an efficient workflow to achieve fast and reliable depth imaging in layered geology; this involves the decomposition of the near-surface velocity into short-, medium-, and long-wavelength terms followed by reflection velocity analysis and anisotropic parameter scanning. The long-wavelength components are solved by dynamic velocity analysis, whereas the medium- and short-wavelength terms are evaluated by surface-consistent analysis applied to refracted and reflected data. Interaction with seismic interpreters and geology-consistent updates mitigates the possibility of introducing errors in areas not covered by wells. The workflow is applied to a structure-controlled wadi in central Saudi Arabia showing complex near-surface conditions and imaging problems. The study incorporates high-resolution helicopter-borne transient electromagnetic data that are used to constrain seismic traveltime inversion through cross-gradient structural regularization (joint inversion). Fast and robust depth imaging constrained by well data is obtained through accurate estimation of near-surface velocities, anisotropy, and geology-consistent analysis.

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Gaussian beam migration: Prestack, common‐shot, TTI, true amplitude in angular domain

Cited by 3 publications

References 3 publications

Frequency-domain elastic full waveform inversion for VTI media

Frequency-domain elastic full waveform inversion for VTI media

Least-squares Reverse-time Migration

Near-surface and anisotropy modeling for efficient land seismic depth imaging in low-relief geology

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